Study Identifies Epigenetic Markers That Indicate an Elevated Risk of Type 2 Diabetes

Scientists from several partner institutes of the German Center for Diabetes Research (DZD) have identified specific epigenetic markers in the blood that can indicate which individuals with prediabetes face a heightened risk of type 2 diabetes. Their findings suggest that a simple blood test could become a practical tool for early detection of those most likely to develop type 2 diabetes, bridging molecular medicine with modern data analysis.

Prediabetes provides a crucial period during which lifestyle changes can prevent or reverse disease progression. However, not all individuals with prediabetes share the same level of risk. Some progress rapidly toward type 2 diabetes or related complications, while others remain metabolically stable. Accurate risk evaluation, therefore, plays a central role in targeting interventions effectively.

Previous research from the DZD had classified prediabetes into six metabolic clusters—three moderate-risk and three high-risk groups—based on glucose tolerance, insulin response, and imaging data. This classification provided valuable insight but relied on time-intensive examinations unsuitable for routine use. “This detailed classification is of great value, but is simply too time-consuming for routine practice,” said Meriem Ouni, co-author of the study published in Biomarker Research. The team aimed to determine whether circulating biomarkers could replace these complex procedures and still reveal the same risk information.

To achieve this, researchers applied DNA methylation analyses combined with advanced computational methods to blood samples from people with known prediabetes risk profiles. Across multiple study cohorts, they identified 1,557 epigenetic markers that accurately distinguished high-risk clusters with approximately 90 percent precision, even in an independent validation cohort. Many markers proved specific to individual clusters and reflected distinct biological pathways linked to type 2 diabetes, chronic inflammation, and heart or kidney disease.

According to senior author Prof. Annette Schürmann, the results show that these epigenetic patterns function as an “effective early warning system.” They reveal not only a person’s current metabolic condition but also signal how the disease may evolve over time. The researchers now plan to narrow the number of markers and design a diagnostic chip to enable practical, cost-effective identification of risk clusters in clinical settings, making population-wide early prevention more feasible.